Built a robust outbound system
Built a full agentic outreach engine â complex logic, multiple data sources, edge-case handling. My n8n version took months. Rebuilt it in Antigravity: 47 minutes to a working system, a week to harden it, same-or-better results. No hype. Just reality-shifted execution. pain â outcome: Pain: SDRs wasting 10â20 hours/week on copy-paste, bad signals, and manual personalization. Fix: Replace repetitive operator work with an agentic workflow that plans, reasons, and self-corrects. Outcome: Projects that were 20â40 hours become 2 hours. Multiple tools collapse into one system. More output, same headcount. How the change actually shows up (practical bullets): More calls: personalization at scale (real context, not templates) â reply and booking lift. Less ops drag: data entry, enrichment, routing automated â ops time cut dramatically. Fewer tools: one agentic system chains research â outreach â follow-up â triage. Resilience: system can self-correct and improve iterations without you babysitting each run. Reality check (be brutally honest): AI isnât perfect. It still makes mistakes. But the speed of iteration now means you fix errors fast and gain leverage far quicker than you did last year. Ignoring AI isnât neutral â itâs falling behind. The winners will be teams that treat AI like an operator, not an assistant. Quick blueprint (what to build first): Signal layer â scrape hiring, posts, fundraising, product updates. If they signal, theyâre worth outreach. Context layer â pull recent content (LinkedIn posts, blog, news) and compress to a 1-line icebreaker. Agent logic â rules for sequencing channels, cadence, and self-correction on failures. Quality layer â automated checks: validate emails, detect tone problems, flag risky sends. Measurement â bookings, replies, time saved per SDR. Optimize for bookings and pipeline, not opens. Agency owner: stop wasting 2 hours/day per rep on research. That can become 10Ă more leads qualified without hiring.